Abstract

Observations of conditions at the ocean surface have been made for centuries, contributing to some of the longest instrumental records of climate change. Most prominent is the climate data record of sea surface temperature (SST), which is itself essential to the majority of activities in climate science and climate service provision. A much wider range of surface marine observations is available however, providing a rich source of data on past climate. We present a general error model describing the characteristics of observations used for the construction of climate records, illustrating the importance of multi-variate records with rich metadata for reducing uncertainty in climate data records. We describe the data and metadata requirements for the construction of stable, multi-century marine climate data records for variables important for describing the changing climate: SST, mean sea level pressure, air temperature, humidity, winds, clouds and waves. Available sources of surface marine data are reviewed in the context of the error model. We outline the need for a range of complementary observations, including very high quality observations at a limited number of locations and also observations that sample more broadly but with greater uncertainty. We describe how high-resolution modern records, particularly those of high-quality, can help to improve the quality of observations throughout the historical record. We recommend the extension of internationally-coordinated data management and curation to observation types that do not have a primary focus of the construction of climate records. The benefits of reprocessing the existing surface marine climate archive to improve and quantify data and metadata quality and homogeneity. We also recommend the expansion of observations from research vessels and high quality moorings, routine observations from ships and from data and metadata rescue. Other priorities include: field evaluation of sensors; resources for the process of establishing user requirements and determining whether requirements are being met; and research to estimate uncertainty, quantify biases and to improve methods of construction of climate data records. The requirements developed in this paper encompass specific actions involving a variety of stakeholders, including funding agencies, scientists, data managers, observing network operators, satellite agencies and international co-ordination bodies.

Highlights

  • Observations of environmental conditions near the ocean surface have been made from ships for centuries, and more recently from a wider range of observing platforms, including satellites

  • The most well-known long term marine climate record is that of sea surface temperature (SST), but there are observations of air temperature, pressure, humidity, wind, clouds, waves, and weather conditions that have been used to generate climate records

  • Observing Systems Capability Analysis and Review Tool (OSCAR) considers a range of different application areas, other areas related to climate include climate science, applications and services, but climate monitoring is the most relevant to the construction of long-term climate records

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Summary

INTRODUCTION

Observations of environmental conditions near the ocean surface have been made from ships for centuries, and more recently from a wider range of observing platforms, including satellites. Quality Control Initial checking can identify reports with incorrect values for date, time and position, unphysical values for elements or incorrectly coded parameters or metadata If these errors are systematic, it may be possible to re-translate the available observation source, or to provide feedback to the data provider and obtain a revised version. Examples include: the clustering of reports likely to be made on the same platform by ship tracking (Carella et al, 2017); the inference of data units or reporting precision from the distribution of reported values (Rhines et al, 2015); or the assignment of observing methods based on the data characteristics (Carella et al, 2018) Such indirect methods of deducing metadata should be supported by full descriptions including observing instructions, information on instruments, their locations and installation and documenting each stage of report coding and recoding. Accurate SSTs, in the presence of dust or other high aerosol loading

Distributed but interoperable data
Findings
Funding agencies JCOMM
Full Text
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